On Criteria for Occurrence of Azeotropes in Isothermal and Isobaric Binary Systems
Bibliographic record
Abstract
Abstract Criteria are developed for the occurrence of azeotropes in binary nonelectrolyte systems for both isothermal and isobaric situations in terms of liquid‐phase activity coefficients at infinite dilution (γ∞). In the case of isothermal systems at temperature T, for a positive azeotrope, γ∞lvc≥ p*mvc/p*lvc where lvc refers to the less volatile component, mvc to the more volatile component, and p* to saturation vapour pressure at T; for a negative azeotrope, γ∞mvc≤ p*lvc/p*mvc. In the case of isobaric systems at pressure P, for a minimum‐boiling azeotrope, γ∞lvc(TBmvc) ≥ P/p*lvc(TBmvc), where TB refers to the boiling point at P; for a maximum‐boiling azeotrope, γ∞mvc (TBlvc) ≤ P/p*mvc(TBlvc). The criteria are also given in terms of the parameters of selected correlations for the excess molar Gibbs function (gE). Examples of the use of the criteria are provided. Various methods that generate values of γ∞ can be used in conjunction with the criteria, for example, in screening procedures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".